Research on multi-objective network optimisation of power material distribution based on the improved ε constraint method
by Guanghui Wang; Yumin Li
International Journal of Computing Science and Mathematics (IJCSM), Vol. 16, No. 3, 2022

Abstract: Aiming at the multi-objective distribution path optimisation of power materials, a multi-objective distribution planning system based on the improved ε constraint algorithm is designed. Then a local power material transportation example in China is selected to simulate and test the system. The results show that the optimal solution routes obtained by the system and the planning system based on the naïve ε constraint algorithm are completely consistent except for the material demand node j₅, j₇, j₈ . At the same time, the average total transportation time and average total transportation cost of the system within ε₃ calculation accuracy are 386.55 min and 283.06 k$ respectively, which are 4.62%, 9.41%, 6.33% and 1.56%, 6.98%, 3.45% less than the corresponding data of the optimal solution of the system based on the naïve ε constraint algorithm, particle swarm optimisation algorithm and fast RCNN algorithm, respectively. The data show that the algorithm can shorten the time and cost of transportation tasks, and the planning effect is better.

Online publication date: Wed, 11-Jan-2023

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computing Science and Mathematics (IJCSM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com